长江流域资源与环境 >> 2021, Vol. 30 >> Issue (8): 2038-2037.doi: 10.11870/cjlyzyyhj202108024

• 自然灾害 • 上一篇    

淮海经济区PM 2.5时空特征及影响因素

宋洁1,徐建斌 2* ,刘佳 3,仇方道 4   

  1.  (1.中山大学 地理科学与规划学院,广东 广州 510275;2.山西财经大学 资源环境学院,山西 太原 030006;
    3.山西省大气探测技术保障中心,山西 太原 030002;4.江苏师范大学 地理测绘与城市规划学院,江苏 徐州 221116)
  • 出版日期:2021-08-20 发布日期:2021-09-06

Spatial and Temporal Characteristics and Influencing Factors of PM 2.5 in Huaihai Economic Zone

SONG Jie 1,XU Jian-bin 2,LIU Jia 3,QIU Fang-dao 4   

  1. (1. School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China; 2. College of Resources and Environment,
     Shanxi University of Finance Economics, Taiyuan 030006, China; 3. Atmospheric Sounding Technology Assurance Center of Shanxi Province,
     Taiyuan 030002, China; 4. School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China)
  • Online:2021-08-20 Published:2021-09-06

摘要: PM 2.5对区域环境和人体健康有着重要影响,淮海经济区作为东部沿海经济发展带的重要支撑部分,剖析其PM 2.5时空特征及其影响因素对于京津冀和长三角城市群开展区域空气污染的联防有着重要意义。首先采用时间序列分析对研究区PM 2.5浓度特征进行分析,其次利用空间分析方法分析了淮海经济区PM 2.5时空特征,最后基于淮海经济区PM 2.5空间自相关特征,进一步采用地理加权回归模型探究了PM 2.5浓度的影响因素及其空间异质性。结果表明:(1)淮海经济区逐日PM 2.5浓度值呈现出周期性的脉冲型起伏变化规律,整体呈现出冬秋季高、春夏低的“U”型趋势。逐日PM 2.5浓度振荡周期短周期为2~3 d,长周期为6~7 d。(2)淮海经济区PM 2.5浓度的空间局部相关性呈现出周期性的变化规律。全年热点区域主要集中在研究区西北的菏泽市和西南的徐州市,冷点区则主要集中在沿海区域。(3)淮海经济区PM 2.5浓度影响因素主要包括平均气温、平均降水、平均风速、林地比例和路网密度等因素,不同因素对PM2.5浓度影响存在显著的空间异质性。

Abstract: PM 2.5 exerts significant impact on the regional environment and human health. Huaihai Economic Zone serves as a core that supports the development of the eastern coastal economic development zone so the analysis of its temporal and spatial characteristics of PM 2.5 and its influencing factors are of great significance to carry out the joint prevention of regional air pollution in the Beijing-Tianjin-Hebei region and the Yangtze River Delta urban agglomeration. Firstly, this paper uses time series analysis to analyze the characteristics of PM 2.5 concentration in the study area. Secondly, spatial analysis is used to analyze the temporal and spatial characteristics of PM 2.5 in the Huaihai Economic Zone. Finally, this paper further explores the influencing factors of PM 2.5 concentration and its spatial heterogeneity by using a geographical weighted regression model based on the spatial autocorrelation characteristics of PM 2.5 in the Huaihai Economic Zone. The results show that: (1)The daily PM 2.5 concentration in Huaihai Economic Zone shows a periodic pulsed fluctuation rule, and the overall trend is “U” shaped, high in winter and autumn and low in spring and summer. The oscillation period of daily PM 2.5 concentration is 2-3 days in a short period and 6-7 days in a long period. (2)The spatial local correlation of PM 2.5 concentration in Huaihai Economic Zone shows a periodic changing rule. Hot spots throughout the year are mainly concentrated in Heze City in the northwest and Xuzhou City in the southwest of the study area while cold spots are mainly in coastal areas. (3)The influencing factors of PM 2.5 concentration in Huaihai Economic Zone mainly include average air temperature, average precipitation, average wind speed, proportion of forest land and road network density. Different factors have significant spatial heterogeneity on the influence of PM 2.5 concentration.

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